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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data
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directly and relate them to structural and functional outcomes. In parallel, you will develop new sensors for intracellular potassium concentration leveraging AI based protein design algorithms. Techniques
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adapted based on the abilities and needs of patients. Moreover, automatic intelligent algorithms will be developed in to make the control intuitive, natural and adaptive. Such that the model can learn new
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Optimization-based control explores the use of optimization algorithms for feedback control of dynamical systems. For example, model predictive control (MPC) is a widely used optimization-based control method
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in handling stall onset and recovery. This project will focus on the modelling and control of hysteresis effects, under the framework of numerical optimal control. The aim is to develop advanced
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Deadline: Applications accepted all year round Details The aim of this project is to develop scalable and efficient techniques and algorithms for localisation in different environments, based on data in
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information extraction. Advanced algorithms will be developed to obtain useful information such as the 3D flame topology and spread velocity. The candidate should have a good background in mathematics and they
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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industry. A damage-tolerant approach is being developed to predict the fatigue life and optimise the design of thinner parts. Cracks are allowed in parts of an aircraft but must be frequently monitored
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. The ultimate goal is to develop theory and methods for the construction of low-complexity invariant sets, using computationally tractable algorithms. Funding Notes This is a self-funded research project. We